Project description:Meningiomas are typically considered a benign tumor that can be cured by complete surgical resection; however, a percentage of patients have recurrent disease, even after apparently complete resections. These patients require additional surgeries, radiation therapy, chemotherapy, or a combination of all three. The ability to recognize these patients prior to recurrence would promote earlier use of adjuvant therapy, thus improving overall patient outcome. Unfortunately, identification of meningiomas with this more aggressive phenotype is difficult, and standard histopathological techniques rarely suffice. The identification of genetic and molecular parameters that can help to define these more aggressive tumors would improve prognostication and treatment planning for patients with meningiomas. 1. Establish gene profiles for benign (grade 1) and aggressive (grades 2 and 3) meningiomas. 2. Determine if there are particular expression profiles that can help differentiate between benign and aggressive meningiomas. 3. Determine if there is/are specific gene(s) whose expression is/are altered in benign vs aggressive tumors. 4. Determine if there is a correlation between specific genetic abnormalities in these tumors (as analyzed by fluorescent in situ hybridization; FISH) and gene expression profiles. Our overall hypothesis is that there are molecular and biochemical changes that can be used to identify meningiomas that will have a more aggressive clinical course. Specific Aims 1 and 2: RNA from flash frozen or RNA-later preserved tissue (from all three grades of meningiomas) has been used for RNA isolation using standard protocols. RNA quantity has been determined using a RiboGreen RNA quantitation Kit (Molecular Probes), and RNA quality has been demonstrated using standard formaldehyde gels. These samples will be sent to the NINDS/NIMH microarray consortium for Affymetrix microarray analyses. Data analysis will be done using GeneSpring software (Silicon Genetics, Inc.) with assistance from consortium personnel. Specific Aim 3: Differentially expressed genes identified through microarray analyses will be analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Real time qRT-PCR is a standard technique used in our laboratory for gene expression analysis. Specific Aim 4: FISH analyses of paraffin-embedded tissue has been completed for 77 tumors. We have frozen tissue from a number of these patients. RNA from these samples will be used for microarray analyses (Specific Aims 1-3). The results of Speicifc Aims 1 and 2 will affect how we perform our correlation analyses. This will be done with the assistance of contracted statistical personnel

Project description:Meningiomas are typically considered a benign tumor that can be cured by complete surgical resection; however, a percentage of patients have recurrent disease, even after apparently complete resections. These patients require additional surgeries, radiation therapy, chemotherapy, or a combination of all three. The ability to recognize these patients prior to recurrence would promote earlier use of adjuvant therapy, thus improving overall patient outcome. Unfortunately, identification of meningiomas with this more aggressive phenotype is difficult, and standard histopathological techniques rarely suffice. The identification of genetic and molecular parameters that can help to define these more aggressive tumors would improve prognostication and treatment planning for patients with meningiomas. 1. Establish gene profiles for benign (grade 1) and aggressive (grades 2 and 3) meningiomas. 2. Determine if there are particular expression profiles that can help differentiate between benign and aggressive meningiomas. 3. Determine if there is/are specific gene(s) whose expression is/are altered in benign vs aggressive tumors. 4. Determine if there is a correlation between specific genetic abnormalities in these tumors (as analyzed by fluorescent in situ hybridization; FISH) and gene expression profiles. Our overall hypothesis is that there are molecular and biochemical changes that can be used to identify meningiomas that will have a more aggressive clinical course. Specific Aims 1 and 2: RNA from flash frozen or RNA-later preserved tissue (from all three grades of meningiomas) has been used for RNA isolation using standard protocols. RNA quantity has been determined using a RiboGreen RNA quantitation Kit (Molecular Probes), and RNA quality has been demonstrated using standard formaldehyde gels. These samples will be sent to the NINDS/NIMH microarray consortium for Affymetrix microarray analyses. Data analysis will be done using GeneSpring software (Silicon Genetics, Inc.) with assistance from consortium personnel. Specific Aim 3: Differentially expressed genes identified through microarray analyses will be analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Real time qRT-PCR is a standard technique used in our laboratory for gene expression analysis. Specific Aim 4: FISH analyses of paraffin-embedded tissue has been completed for 77 tumors. We have frozen tissue from a number of these patients. RNA from these samples will be used for microarray analyses (Specific Aims 1-3). The results of Speicifc Aims 1 and 2 will affect how we perform our correlation analyses. This will be done with the assistance of contracted statistical personnel. Keywords: other

Project description:Meningiomas are typically considered a benign tumor that can be cured by complete surgical resection; however, a percentage of patients have recurrent disease, even after apparently complete resections. These patients require additional surgeries, radiation therapy, chemotherapy, or a combination of all three. The ability to recognize these patients prior to recurrence would promote earlier use of adjuvant therapy, thus improving overall patient outcome. Unfortunately, identification of meningiomas with this more aggressive phenotype is difficult, and standard histopathological techniques rarely suffice. The identification of genetic and molecular parameters that can help to define these more aggressive tumors would improve prognostication and treatment planning for patients with meningiomas. 1. Establish gene profiles for benign (grade 1) and aggressive (grades 2 and 3) meningiomas. 2. Determine if there are particular expression profiles that can help differentiate between benign and aggressive meningiomas. 3. Determine if there is/are specific gene(s) whose expression is/are altered in benign vs aggressive tumors. 4. Determine if there is a correlation between specific genetic abnormalities in these tumors (as analyzed by fluorescent in situ hybridization; FISH) and gene expression profiles. Our overall hypothesis is that there are molecular and biochemical changes that can be used to identify meningiomas that will have a more aggressive clinical course. Specific Aims 1 and 2: RNA from flash frozen or RNA-later preserved tissue (from all three grades of meningiomas) has been used for RNA isolation using standard protocols. RNA quantity has been determined using a RiboGreen RNA quantitation Kit (Molecular Probes), and RNA quality has been demonstrated using standard formaldehyde gels. These samples will be sent to the NINDS/NIMH microarray consortium for Affymetrix microarray analyses. Data analysis will be done using GeneSpring software (Silicon Genetics, Inc.) with assistance from consortium personnel. Specific Aim 3: Differentially expressed genes identified through microarray analyses will be analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Real time qRT-PCR is a standard technique used in our laboratory for gene expression analysis. Specific Aim 4: FISH analyses of paraffin-embedded tissue has been completed for 77 tumors. We have frozen tissue from a number of these patients. RNA from these samples will be used for microarray analyses (Specific Aims 1-3). The results of Speicifc Aims 1 and 2 will affect how we perform our correlation analyses. This will be done with the assistance of contracted statistical personnel Keywords: other

Project description:Background: Meningiomas account for about 27% of primary brain tumors, making them one of the most common brain tumor. They are most common in people between the ages of 40 and 70 and are more common in women than in men. Most meningiomas (90%) are categorized as benign tumors, with the remaining 10% being atypical or malignant. Multiple classifications exist today, but the most commonly used is the World Health Organization’s (WHO) which classifies meningiomas into three histological grades: grade I (benign), grade II (atypical), and grade III (anaplastic) in accordance with the clinical prognosis. Most of these subtypes behave similarly, however anaplastics are the most aggressive. The ability to distinguish benign from atypical and anaplastic tumors is important because of its impact on treatment decisions. A molecular based classification system has the likelihood of being a better prognostic indicator and is useful for identifying alterations in pathways and networks that drive tumor progression and growth. The information obtained can potentially be translated into more effective and less toxic targeted therapies. We tested a method for genome wide expression profiling of formalin-fixed, paraffin-embedded tissues. We applied the method to the analysis of the clinical outcome of meningioma tumor. Materials and Methods: The training set consisted of tissue samples from 63 patients who were consecutively treated with surgery for meningioma between 1990 and 2005. For each patient data on clinical outcomes and formalin-fixed, paraffin-embedded blocks of tumor were available. The validation set included tissue samples from 189 patients with meningioma who consecutively underwent surgery between 1992 and 2006. We used a custom 60-mer amino modified oligo- array, containing 912 probes, a lot of which specific for genes commonly altered in cancer. Functional annotation was performed by means of gene set enrichment analysis (GSEA, www. broad.mit.edu/gsea/). Survival analyses were performed with the use of the log-rank test and Cox regression modeling. All analyses were performed with the use of GenePattern. Results: We investigated whether gene-expression profiles of meningioma tumors were associated with the clinical outcome. Using a standard leaveone- out cross-validation procedure, we found the meningioma signature to be significantly correlated with survival (P = 0.0001). The survival correlated signature contained 219 genes and was tested in the validation set. Conclusion: These results support the validity of the survival signature and highlight the potential role of tumoral meningioma tissue in predicting the outcome for patients with meningioma tumors.

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Transcription profiling of human meningiomas with aggressibe and non aggressive phenotypes

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